[R] understanding the verbose output in nlme
Greg Distiller
gregd at stats.uct.ac.za
Thu Jun 1 15:57:48 CEST 2006
Hi
I have found some postings referring to the fact that one can try and
understand why a particular model is failing to solve/converge from the
verbose output one can generate when fitting a nonlinear mixed model. I am
trying to understand this output and have not been able to find out much:
**Iteration 1
LME step: Loglik: -237.4517 , nlm iterations: 22
reStruct parameters:
subjectno1 subjectno2 subjectno3 subjectno4 subjectno5
subjectno6
-0.87239181 2.75772772 -0.72892919 -10.36636391 0.55290322
0.09878685
PNLS step: RSS = 60.50164
fixed effects:2.59129 0.00741764 0.57155
iterations: 7
Convergence:
fixed reStruct
5.740688 2.159285
I know that the Loglik must refer to the value of the log likelihood
function, that the values after "fixed effects" are the parameter estimates,
and that the bit after Convergence obviously has something to so with the
convergence criteria for the fixed effects and the random effects structure.
I did manage to find a posting where somebody said that the restruct
parameter is the log of the relative precision of the random effects? The
one thing that is a bit confusing to me is that it appears as if the fixed
effects convergence must be zero (or close to it) as one would expect but in
one of my converged models the output showed a restruct value of 0.72 ?
Then I have no idea what the numbers under subjectno1-6 are, especially as I
have 103 subjects in the data!
Can anyone help shed some light on this output and how it can be used to
diagnose issues with a model?
Many thanks
Greg
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